Individual tree dataset from airborne laser scanning data

<h1>General description</h1> <p>Data about individual tree segments detected from the Finnish national 5 pt/m^2 airborne laser scanning data. The dataset contains 281304 individual trees from a test site of 3km x 3km located in Padasjoki, Finland. The ALS data has been collected in 2019.</p> <h1>Data description</h1> <p>The individual tree segment dataset has been published as a CSV file. The tree height, DBH, stem volume and above-ground biomass have been predicted using Random Forest Machine Learning models. The rest of the features have been calculated directly from the ALS point cloud. The CSV file contains the following columns:</p> <ul> <li><strong>LX</strong> and <strong>LY</strong>: tree location (location of max height in the canopy height model) in the ETRS-TM35FIN coordinate reference system (EPSG:3067)</li> <li><strong>Hmax</strong>: tree height (based on highest returns)</li> <li><strong>Gele</strong>: ground elevation at tree location (interpolated from ground points)</li> <li><strong>lowBranch</strong>: height of lowest branch (limited accuracy)</li> <li><strong>crownV</strong>: crown volume as 3D convex hull</li> <li><strong>species</strong>: predicted species: 1 = pine, 2 = spruce, 3 = deciduous tree</li> <li><strong>H</strong>: predicted tree height</li> <li><strong>DBH</strong>: predicted diameter at breast height</li> <li><strong>Volume</strong>: predicted stem volume</li> <li><strong>Biomass</strong>: predicted above-ground biomass (dry mass)</li> </ul> <h1>Citation</h1> <p>Any scientific publication using the data should cite the following paper:</p> <p>Hyypp&auml;, M., Turppa, T., Hyyti, H., Yu, X., Handolin, H., Kukko, A., Hyypp&auml;, J., &amp; Virtanen, J. -P. (2024). Concepts Towards Nation-Wide Individual Tree Data and Virtual Forests. <em>ISPRS International Journal of Geo-Information</em>, <em>13</em>(12), 424. https://doi.org/10.3390/ijgi13120424</p>